Downscaling top-down CO2 emissions and sinks in China empowered by hybrid training
Atmospheric CO2-based top-down approaches enable objective evaluation of climate mitigation efforts but face dual constraints: sparse monitoring limits spatial resolution, while emission heterogeneity hampers downscaling. To enhance downscaling accuracy, we present a hybrid training method integrating multi-resolution inverse fluxes—national-scale coarse grids with fine-scale grids (Shanxi/Jiangsu). Experiments show hybrid training outperforms conventional approaches, increasing R² from 0.56 to 0.61 with 2.7%-area fine grids and reducing prediction biases compared to data fusion without high-resolution inputs while vastly exceeding nearest-neighbor interpolation (R² = 0.39). By combining gap-filled CO/NO2 columns, nighttime lights, population density, vegetation indices, and meteorological data, we downscaled national 45 km eight-day CO2 fluxes to daily 10 km resolution. The derived dataset reveals emission inequities: top 20% cities contribute more than 50% of national emissions, exposing regional capacity disparities. This framework leverages expanding CO2 monitoring networks to progressively refine spatiotemporal resolution, enabling city-level verification of mitigation actions.
Authors
- Weihua Pan (ORCID: https://orcid.org/0000-0001-8077-023X)
- Deying Wang
- Fugang Li (ORCID: https://orcid.org/0000-0002-9986-9608)
- Lei Ren (ORCID: https://orcid.org/0000-0002-6335-9753)
- Bo Peng (ORCID: https://orcid.org/0000-0002-9014-7369)
- Da‐Lin Zhang (ORCID: https://orcid.org/0000-0003-1725-283X)
- Junting Zhong (ORCID: https://orcid.org/0000-0002-4109-3405)
- Qingyan Chen
- Fei Yu (ORCID: https://orcid.org/0000-0003-4262-3225)
- Lifeng Guo
- Changhong Miao (ORCID: https://orcid.org/0000-0002-3406-8877)
- Xiliang Zhang (ORCID: https://orcid.org/0000-0003-0822-2794)
- Chongyuan Wu
- Xiaoye Zhang (ORCID: https://orcid.org/0000-0003-1802-3385)
- Lichun Li (ORCID: https://orcid.org/0000-0002-6661-1352)
- Lingyun Zhu (ORCID: https://orcid.org/0000-0002-1304-012X)
- Jiaying Li (ORCID: https://orcid.org/0000-0002-9424-0149)
Institutions
- Climate Central (US)
- Henan University (CN)
- Jiangsu Provincial Meteorological Bureau (CN)
- Jiangsu Institute of Meteorological Sciences (CN)
- Chinese Academy of Meteorological Sciences (CN)
- Guizhou Provincial Meteorological Bureau (CN)
- Fujian Provincial Hospital (CN)
- Qinghai Meteorological Bureau (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- npj Climate and Atmospheric Science
- Published
- 2025-05-23
- DOI
- https://doi.org/10.1038/s41612-025-01071-3
- Citations
- 5
- Primary Topic
- Atmospheric and Environmental Gas Dynamics
- Type
- article
- Field-Weighted Citation Impact
- 5.53
Funders
- National Natural Science Foundation of China